code: def _setup_editor(self):
      super()._setup_editor()
  
      antonyms = [
          ("progressive", "conservative"),
          ("positive", "negative"),
          ("defensive", "offensive"),
          ("rude", "polite"),
          ("optimistic", "pessimistic"),
          ("stupid", "smart"),
          ("negative", "positive"),
          ("unhappy", "happy"),
          ("active", "passive"),
          ("impatient", "patient"),
          ("powerless", "powerful"),
          ("visible", "invisible"),
          ("fat", "thin"),
          ("bad", "good"),
          ("cautious", "brave"),
          ("hopeful", "hopeless"),
          ("insecure", "secure"),
          ("humble", "proud"),
          ("passive", "active"),
          ("dependent", "independent"),
          ("pessimistic", "optimistic"),
          ("irresponsible", "responsible"),
          ("courageous", "fearful"),
      ]
  
      self.editor.add_lexicon("antonyms", antonyms, overwrite=True)
  
      synonyms = [
          ("smart", "intelligent"),
          ("optimistic", "hopeful"),
          ("brave", "courageous"),
          ("adorable", "cute"),
          ("huge", "enormous"),
          ("intelligent", "clever"),
          ("lazy", "indolent"),
          ("rude", "impolite"),
          ("thin", "lean"),
          ("sad", "unhappy"),
          ("little", "small"),
      ]
  
      self.editor.add_lexicon("synonyms", synonyms, overwrite=True)
  
      comp = [
          "smarter",
          "better",
          "worse",
          "brighter",
          "bigger",
          "louder",
          "longer",
          "larger",
          "smaller",
          "warmer",
          "colder",
          "thicker",
          "lighter",
          "heavier",
      ]
  
      self.editor.add_lexicon("compare", comp, overwrite=True)
  
      nouns = [
          "humans",
          "cats",
          "dogs",
          "people",
          "mice",
          "pigs",
          "birds",
          "sheep",
          "cows",
          "rats",
          "chickens",
          "fish",
          "bears",
          "elephants",
          "rabbits",
          "lions",
          "monkeys",
          "snakes",
          "bees",
          "spiders",
          "bats",
          "puppies",
          "dolphins",
          "babies",
          "kittens",
          "children",
          "frogs",
          "ants",
          "butterflies",
          "insects",
          "turtles",
          "trees",
          "ducks",
          "whales",
          "robots",
          "animals",
          "bugs",
          "kids",
          "crabs",
          "carrots",
          "dragons",
          "mosquitoes",
          "cars",
          "sharks",
          "dinosaurs",
          "horses",
          "tigers",
      ]
      self.editor.add_lexicon("nouns", nouns, overwrite=True)
  
      adjectives = [
          "good",
          "great",
          "excellent",
          "amazing",
          "extraordinary",
          "beautiful",
          "fantastic",
          "nice",
          "awful",
          "bad",
          "horrible",
          "weird",
          "rough",
      ]
      self.editor.add_lexicon("adjectives", adjectives, overwrite=True)
  
      intens_adj = [
          "very",
          "really",
          "absolutely",
          "truly",
          "extremely",
          "quite",
          "incredibly",
          "amazingly",
          "especially",
          "exceptionally",
          "unbelievably",
          "utterly",
          "exceedingly",
          "rather",
          "totally",
          "particularly",
      ]
      intens_verb = [
          "really",
          "absolutely",
          "truly",
          "extremely",
          "especially",
          "utterly",
          "totally",
          "particularly",
          "highly",
          "definitely",
          "certainly",
          "genuinely",
          "honestly",
          "strongly",
          "sure",
          "sincerely",
      ]
  
      self.editor.add_lexicon("intens_adj", intens_adj, overwrite=True)
      self.editor.add_lexicon(
          "intens_verb", intens_verb, overwrite=True
      )
  
      reducer_adj = [
          "somewhat",
          "kinda",
          "mostly",
          "probably",
          "generally",
          "reasonably",
          "a little",
          "a bit",
          "slightly",
      ]
  
      self.editor.add_lexicon(
          "reducer_adj", reducer_adj, overwrite=True
      )
  
      subclasses = [
          (
              "vehicles",
              [
                  "cars",
                  "trucks",
                  "jeeps",
                  "bikes",
                  "motorcycles",
                  "tractors",
                  "vans",
                  "SUVs",
                  "minivans",
                  "bicycles",
              ],
          ),
          (
              "animals",
              [
                  "dogs",
                  "cats",
                  "turtles",
                  "lizards",
                  "snakes",
                  "fish",
                  "hamsters",
                  "rabbits",
                  "guinea pigs",
                  "ducks",
              ],
          ),
          (
              "clothes",
              [
                  "jackets",
                  "pants",
                  "shirts",
                  "skirts",
                  "t-shirts",
                  "raincoats",
                  "sweaters",
                  "jeans",
                  "sweatpants",
              ],
          ),
      ]
  
      subclasses = [
          (a, b[i]) for a, b in subclasses for i in range(len(b))
      ]
      self.editor.add_lexicon("subclasses", subclasses, overwrite=True)
  
imports: from typing import Optional, Tuple, Iterable, Callable, Union
  import itertools
  import numpy
  from checklist.test_suite import TestSuite
  from checklist.test_types import MFT, INV, DIR, Expect
  from checklist.perturb import Perturb
  from allennlp.confidence_checks.task_checklists.task_suite import TaskSuite
  from allennlp.confidence_checks.task_checklists import utils
  from allennlp.predictors import Predictor
label_desc: Use image node_id 7 for calling the TextualEntailmentSuite obj's underlying member method code with example usage: obj._setup_editor() without return types